## [1] 0.3931177
Not all that different from the example completed in the textbook, a slightly higher than one third of Solano County is overburdened by the cost of housing in the Bay Area. This number is higher than that of the Bay Area at large as was calculated in the textbook.
## [1] 168594477
The number above represents the dollar amount that would be necessary to alleviate the excess burden of housing cost beyond 30% of one’s income for the entirety of Solano County, California. The number, more than 3.5 Billion dollars, which is not insignificant in the slightest. It is confirmed again and again that housing costs in the Bay Area area causing great hardship for many residents living there.
## [1] 0.3668098
Once again, roughly one third of households without children are burdened by housing cost.
## [1] 289769776
This number being higher than that of the amount necessary to help those without children
#More Maps to Play with
The above two maps are quite interesting in what they may tell us about these populations. For both household with children and without children, downtown/more dense urban areas are associated with higher overall numbers of burdened households. This is rather intuitive as housing costs are typically higher in urban areas.Once again, city centers and more heavily populated areas tend to be more heavily burdened than others.
This case is slightly different than the others as outlying areas which are likely more rural have a higher total cost of burden than the other groups, but this may just be due to geographical area of the various portions of the study area.
The majority of this district is made up of single family homes, as one can see in the first table provided. While this does not leave an extreme excess of space for supplementary development to potentially house more people in the area. As there are very few commercial businesses located in this area, it may be a prime location for introduction of commercial resources to make the area more complete (in the sense of “Complete Communities”). Overall, small increases to the housing capacity of the parcels in this cbg could help (how ever so slightly) to alleviate pressures caused by lack of affordable housing in the Bay Area. Only roughly 91 more units would be available for others to live in the properties displayed below, but any optimization of resources can be helpful in battling issues such as the affordable housing crisis in San Francisco.
## Reading layer `OGRGeoJSON' from data source `https://data.sfgov.org/api/geospatial/acdm-wktn?method=export&format=GeoJSON' using driver `GeoJSON'
## Simple feature collection with 232455 features and 22 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -122.5147 ymin: 37.70792 xmax: -122.3556 ymax: 37.83607
## geographic CRS: WGS 84
## DATA NAME FIELD NAME
## 1 PROPLOC Property Location
## 2 RP1NBRCDE Neighborhood Code
## 3 RP1PRCLID Block and Lot Number
## 4 RP1VOLUME Volume Number
## 5 RP1CLACDE Property Class Code
## 6 YRBLT Year Property Built
## 7 BATHS Number of Bathrooms
## 8 BEDS Number of Bedrooms
## 9 ROOMS Number of Rooms
## 10 STOREYNO Number of Stories
## 11 UNITS Number of Units
## 12 ZONE Zoning Code
## 13 CONSTTYPE Construction Type
## 14 DEPTH Lot Depth
## 15 FRONT Lot Frontage
## 16 SQFT Property Area in Square Feet
## 17 FBA Basement Area
## 18 LAREA Lot Area
## 19 LOTCODE Lot Code
## 20 REPRISDATE Prior Sales Date (YYMMDD)
## 21 RP1TRACDE Tax Rate Area Code
## 22 OWNRPRCNT Percent of Ownership
## 23 EXEMPTYPE Closed Roll Exemption Type Code
## 24 RP1STACDE Closed Roll Status Code
## 25 RP1EXMVL2 Closed Roll Misc. Exemption Value
## 26 RP1EXMVL1 Closed Roll Homeowner Exemption Value
## 27 ROLLYEAR Closed Roll Year
## 28 RECURRSALD Current Sales Date (YYMMDD)
## 29 RP1FXTVAL Closed Roll Assessed Fixtures Value
## 30 RP1IMPVAL Closed Roll Assessed Improvement Value
## 31 RP1LNDVAL Closed Roll Assessed Land Value
## 32 RP1PPTVAL Closed Roll Assessed Personal Prop Value
## # A tibble: 9 x 3
## # Groups: zoning [9]
## zoning zoning_desc Freq
## <chr> <chr> <int>
## 1 NC-1 NEIGHBORHOOD COMMERCIAL, CLUSTER 1
## 2 NC-2 NEIGHBORHOOD COMMERCIAL, SMALL SCALE 53
## 3 P PUBLIC 7
## 4 RH-1 RESIDENTIAL- HOUSE, ONE FAMILY 628
## 5 RH-1(D) RESIDENTIAL- HOUSE, ONE FAMILY- DETACHED 1092
## 6 RH-1(D)|P RESIDENTIAL- HOUSE, ONE FAMILY- DETACHED|PUBLIC 1
## 7 RH-1(D)|RH… RESIDENTIAL- HOUSE, ONE FAMILY- DETACHED|RESIDENTIAL- HOUSE… 1
## 8 RH-2 RESIDENTIAL- HOUSE, TWO FAMILY 52
## 9 RM-2 RESIDENTIAL- MIXED, MODERATE DENSITY 23
## Freq DESCRIPTION
## 1 7 Apartment 4 units or less
## 2 5 Apartment 5 to 14 Units
## 3 1 Apartmnt & Commercial Store
## 4 12 Commercial Stores
## 5 1 Shopping Center
## 6 1648 Dwelling
## 7 1 Dwellings - Apt 4 units or less
## 8 1 Schools
## 9 74 Flats & Duplex
## 10 14 Flat & Store 4 units or less
## 11 1 <NA>
## 12 2 Flat & Store 5 to 14 units
## 13 1 Office
## 14 1 Public Buildings (Govt)
## 15 1 Clubs,Lodges,Fraternal Organizations
## 16 1 Vacant Lot
## 17 5 <NA>
## 18 46 Vacant Lot Residential
## 19 2 Churches,Convents,Rectories
## 20 7 Misc
## 21 23 Condominium
## 22 4 Condominium Economic Unit
## Reading layer `h9wh-cg3m' from data source `https://data.sfgov.org/resource/h9wh-cg3m.geojson' using driver `GeoJSON'
## Simple feature collection with 1000 features and 2 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -122.5149 ymin: 37.70779 xmax: -122.357 ymax: 37.83062
## geographic CRS: WGS 84
## [1] 2296987
## [1] 91